# 0. 导入必要的库
# TODO
from util import load, get
from lazypredict.Supervised import LazyClassifier

# 1. 加载训练集和测试集
X1_train, X1_test, y1_train, y1_test = load("X1_train, X1_test, y1_train, y1_test", f'{get("Xy_root")}/Xy1')
X2_train, X2_test, y2_train, y2_test = load("X2_train, X2_test, y2_train, y2_test", f'{get("Xy_root")}/Xy2')
X3_train, X3_test, y3_train, y3_test = load("X3_train, X3_test, y3_train, y3_test", f'{get("Xy_root")}/Xy3')

# 2. 使用LazyClassifier进行快速模型评估
print("开始评估所有的模型:")
# TODO
clf1 = LazyClassifier()
scores1, _ = clf1.fit(X1_train, X1_test, y1_train, y1_test)
print("传统方法:", scores1)

clf2 = LazyClassifier()
scores2, _ = clf2.fit(X2_train, X2_test, y2_train, y2_test)
print("HOG方法:", scores2)

clf3 = LazyClassifier()
scores3, _ = clf3.fit(X3_train, X3_test, y3_train, y3_test)
print("VGG16方法:", scores3)

